{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ALD Regression - \n",
    "Anthony DiBenedetto\n",
    "\n",
    "This program uses a neural network to predict the standard deviation from ALD data. The MAE, MSE, and the R^2 value is caculated and printed out in on the of the bottom cells. Also shown is a graph to display what the actual values of testing standard deviation should look like compared to what is predicted. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import Libraries\n",
    "import torch\n",
    "from torch import nn\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "from sklearn.metrics import accuracy_score\n",
    "import torch.onnx\n",
    "import onnx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load the training and test data\n",
    "training_data = (np.load('ALD_Classification_dataset/training_data.npy'))\n",
    "training_std = (np.load('ALD_Classification_dataset/training_std.npy'))\n",
    "\n",
    "testing_data = (np.load('ALD_Classification_dataset/testing_data.npy'))\n",
    "testing_std = (np.load('ALD_Classification_dataset/testing_std.npy'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.046884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.001467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.126835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.000956</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.003506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>0.000653</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>0.036770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>0.002759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>0.009343</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>0.000134</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            0\n",
       "0    0.046884\n",
       "1    0.001467\n",
       "2    0.126835\n",
       "3    0.000956\n",
       "4    0.003506\n",
       "..        ...\n",
       "995  0.000653\n",
       "996  0.036770\n",
       "997  0.002759\n",
       "998  0.009343\n",
       "999  0.000134\n",
       "\n",
       "[1000 rows x 1 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(testing_std)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Covert dtat is Tensor to float 32\n",
    "X_train = torch.tensor(training_data.astype(np.float32))\n",
    "y_train = torch.tensor(training_std.astype(np.float32))\n",
    "\n",
    "X_test = torch.tensor(testing_data.astype(np.float32))\n",
    "y_test = torch.tensor(testing_std.astype(np.float32))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(torch.Size([10000, 120]),\n",
       " torch.Size([1000, 120]),\n",
       " torch.Size([10000]),\n",
       " torch.Size([1000]))"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.shape, X_test.shape, y_train.shape, y_test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create model\n",
    "class std(nn.Module):\n",
    "    def __init__(self, input_features, output_features, hidden_units):\n",
    "        \"\"\" Initialize the model.\n",
    "        Args:\n",
    "            input_features (int): number of input features to the model\n",
    "            output_features (int): number of output features to the model (number output classes)\n",
    "            hidden_units (int): number of hidden units between layers\n",
    "        \"\"\"\n",
    "        super(std, self).__init__()\n",
    "        self.layer_stack = nn.Sequential(\n",
    "            nn.Linear(in_features=input_features, out_features=hidden_units),\n",
    "            nn.ReLU(),\n",
    "            nn.Linear(in_features=hidden_units, out_features=hidden_units),\n",
    "            nn.ReLU(),\n",
    "            nn.Linear(in_features=hidden_units, out_features=output_features)\n",
    "        )\n",
    "\n",
    "    def forward(self, x):\n",
    "        return self.layer_stack(x)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "dummy_input = torch.randn(1, 120)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "std(\n",
       "  (layer_stack): Sequential(\n",
       "    (0): Linear(in_features=120, out_features=480, bias=True)\n",
       "    (1): ReLU()\n",
       "    (2): Linear(in_features=480, out_features=480, bias=True)\n",
       "    (3): ReLU()\n",
       "    (4): Linear(in_features=480, out_features=1, bias=True)\n",
       "  )\n",
       ")"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = std(input_features=120, output_features=1 , hidden_units=480)\n",
    "\n",
    "model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Initialize loss and optimizer \n",
    "loss_fn = nn.L1Loss()\n",
    "\n",
    "\n",
    "optimizer = torch.optim.SGD(params=model.parameters(),\n",
    "                            lr=0.0001,\n",
    "                            momentum=0.9,\n",
    "                            dampening=.01, \n",
    "                            weight_decay=0.0005) \n",
    "                            \n",
    "                            "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 0 | MAE: 0.011353712528944016 | Test MAE: 0.015325168147683144\n",
      "Epoch: 50 | MAE: 0.004901562817394733 | Test MAE: 0.0052132802084088326\n",
      "Epoch: 100 | MAE: 0.00600609602406621 | Test MAE: 0.0033330332953482866\n",
      "Epoch: 150 | MAE: 0.0024443818256258965 | Test MAE: 0.003511267714202404\n",
      "Epoch: 200 | MAE: 0.0008971417555585504 | Test MAE: 0.002250504679977894\n",
      "Epoch: 250 | MAE: 0.002052420750260353 | Test MAE: 0.0019231706392019987\n",
      "Epoch: 300 | MAE: 0.0014185933396220207 | Test MAE: 0.00216570938937366\n",
      "Epoch: 350 | MAE: 0.0017089354805648327 | Test MAE: 0.0017206385964527726\n",
      "Epoch: 400 | MAE: 0.001128035713918507 | Test MAE: 0.0017518512904644012\n",
      "Epoch: 450 | MAE: 0.0013167675351724029 | Test MAE: 0.0018110980745404959\n",
      "Epoch: 500 | MAE: 0.0014163641026243567 | Test MAE: 0.0019069721456617117\n",
      "Epoch: 550 | MAE: 0.001124919974245131 | Test MAE: 0.003022471908479929\n",
      "Epoch: 600 | MAE: 0.0020716460421681404 | Test MAE: 0.001879525021649897\n",
      "Epoch: 650 | MAE: 0.0011372653534635901 | Test MAE: 0.0018348133889958262\n",
      "Epoch: 700 | MAE: 0.0021983813494443893 | Test MAE: 0.0017509900499135256\n",
      "Epoch: 750 | MAE: 0.0008137684781104326 | Test MAE: 0.0014251081738620996\n"
     ]
    }
   ],
   "source": [
    "torch.manual_seed(42)\n",
    "\n",
    "# These lists are created for the graph after the model is trained.\n",
    "epoch_count = []\n",
    "loss_values = []\n",
    "test_loss_values = []\n",
    "\n",
    "# Initialize batch size \n",
    "batch_size = 16\n",
    "num_batches = len(X_train) // batch_size\n",
    "\n",
    "epochs = 800\n",
    "\n",
    "for epoch in range(epochs):\n",
    "    model.train()\n",
    "\n",
    "    # This will shuffle the training data for each epoch\n",
    "    indices = torch.randperm(len(X_train))\n",
    "    X_train = X_train[indices]\n",
    "    y_train = y_train[indices]\n",
    "\n",
    "    for i in range(num_batches):\n",
    "        # Get the current batch\n",
    "        start = i * batch_size\n",
    "        end = (i + 1) * batch_size\n",
    "        X_batch = X_train[start:end]\n",
    "        y_batch = y_train[start:end]\n",
    "    \n",
    "        # Forward pass\n",
    "        y_pred = model(X_batch)\n",
    "\n",
    "        # Calculate the loss\n",
    "        loss = loss_fn(y_pred, y_batch.unsqueeze(1))\n",
    "\n",
    "        optimizer.zero_grad() \n",
    "        \n",
    "        loss.backward()\n",
    "        \n",
    "        optimizer.step()\n",
    "    \n",
    "    # Testing\n",
    "    model.eval()\n",
    "    with torch.inference_mode():\n",
    "        test_pred = model(X_test)       \n",
    "        \n",
    "        # 2. Calculate the loss\n",
    "        test_loss = loss_fn(test_pred, y_test.unsqueeze(1))\n",
    "        if epoch % 50 == 0:\n",
    "            epoch_count.append(epoch)\n",
    "            loss_values.append(loss)\n",
    "            test_loss_values.append(test_loss)\n",
    "            print(f\"Epoch: {epoch} | MAE: {loss.item()} | Test MAE: {test_loss.item()}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(epoch_count, np.array(torch.tensor(loss_values).numpy()), label=\"Train Loss\")\n",
    "plt.plot(epoch_count, test_loss_values, label = \"Test Loss\")\n",
    "plt.title(\"Training and test loss curves\")\n",
    "plt.ylabel(\"Loss\")\n",
    "plt.xlabel(\"Epochs\")\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "with torch.inference_mode():\n",
    "    y_pred = model(X_test)\n",
    "\n",
    "    # Convert the tensor to a numpy array\n",
    "    y_pred = y_pred.detach().numpy()\n",
    "\n",
    "    fig, ax = plt.subplots(figsize=(25,8))\n",
    "\n",
    "    # Plot the actual values in blue\n",
    "    ax.plot(y_test[:200], color='blue', label='Actual',linewidth=1.5)\n",
    "\n",
    "    # Plot the predicted values in orange\n",
    "    ax.plot(y_pred[:200], color='orange', label='Predicted', linewidth=2)\n",
    "\n",
    "    # Set the title and legend\n",
    "    ax.set_title('Actual vs Predicted')\n",
    "    ax.set_ylabel('SD Values')\n",
    "    ax.legend()\n",
    "    ax.set_ylim(0, 0.155)\n",
    "\n",
    "    # Display the plot\n",
    "    plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Mean of y_test: 0.0217\n",
      "Mean of y_pred: 0.0219\n",
      "\n",
      "Median of y_test: 0.0056\n",
      "Median of y_pred: 0.0060\n",
      "\n",
      "R-squared: 0.9921759311316882\n",
      "\n",
      "MSE: 9.0032335720025e-06\n",
      "\n",
      "MAE: 0.001410006545484066\n",
      "Baseline MAE: 0.0241\n"
     ]
    }
   ],
   "source": [
    "import torch.nn.functional as F\n",
    "from sklearn.metrics import r2_score\n",
    "from sklearn.metrics import mean_squared_error\n",
    "from sklearn.metrics import mean_absolute_error\n",
    "\n",
    "# Get the predicted values\n",
    "with torch.inference_mode():\n",
    "    \n",
    "    y_pred = model(X_test)\n",
    "    \n",
    "    print(\"\\nMean of y_test: {:.4f}\".format(y_test.mean()))\n",
    "    print(\"Mean of y_pred: {:.4f}\".format(y_pred.mean()))\n",
    "\n",
    "    print(\"\\nMedian of y_test: {:.4f}\".format(y_test.median()))\n",
    "    print(\"Median of y_pred: {:.4f}\".format(y_pred.median()))\n",
    "\n",
    "    r_squared = r2_score(y_test.unsqueeze(1), y_pred)\n",
    "    print(\"\\nR-squared: {}\".format(r_squared))\n",
    "\n",
    "    mse = mean_squared_error(y_test.unsqueeze(1), y_pred)\n",
    "    print(\"\\nMSE: {}\".format(mse))\n",
    "\n",
    "    mae = mean_absolute_error(y_test.unsqueeze(1), y_pred)\n",
    "    print(\"\\nMAE: {}\".format(mae))\n",
    "\n",
    "    mean_pred = torch.full_like(y_pred, y_test.mean())\n",
    "    mean_mae = F.l1_loss(y_test.unsqueeze(1), mean_pred)\n",
    "    print(\"Baseline MAE: {:.4f}\".format(mean_mae))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(tensor(0.1700), tensor(0.0001))"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max(y_test), min(y_test)"
   ]
  }
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